PROJECT SUMMARY/ABSTRACT Abdominal pain-related functional gastrointestinal disorders (FGIDs; previously called Recurrent Abdominal Pain) affect 10-20% of children and adults worldwide exerting a tremendous economic, social, and emotional burden. Up to 66% of children go on to have similar symptoms as adults. In children, the two most common FGIDs are functional abdominal pain (FAP) and irritable bowel syndrome (IBS - essentially FAP with changes in stooling pattern). Management and treatment are hampered by lack of biomarkers to characterize and understand pathophysiologically what are phenotypically and arbitrarily defined conditions. Previous studies have evaluated IBS, not FAP, and relied primarily on retrospective symptom evaluation and utilized methodology (e.g., 16S sequencing) that limits in depth interrogation of perturbations (e.g., gut dysbiosis) reported in children and adults with IBS. Further, `omics (metabolomics, lipidomics, metaproteomics) data is largely missing from studies of FGIDs and is urgently required - our preliminary data show that it likely provides critical mechanistic insight into the links between abdominal pain symptoms and the pathobiologic alterations of gut dysbiosis, barrier dysfunction, and neuroimmune dysfunction which we and others have described in FGIDs. Our preliminary data support the hypothesis that these alterations can pathobiologically discriminate FGIDs from healthy controls as well as identify disease mechanisms of pain in FGIDs. We propose to build on our previous work and use previously collected prospective abdominal pain and stooling diaries and stool samples collected from a large and well-vetted group of children with FGIDs (IBS n=133, FAP n=47) and healthy controls (HC, n=112). Our Hypothesis is that microbial community characterization and `omics profiling will provide biomarkers to differentiate FGIDs (IBS and FAP) from HC and generate insight into the genesis of pain symptoms (and stooling characteristics in IBS). Our Specific Aims are to use: 1) Global unbiased whole genome shotgun sequencing, metabolomics, lipidomics and metaproteomics (`omics) on stool samples to differentiate children with FGIDs vs HC using classifier models; Sub-Aim ? explore potential differences between FAP and IBS and HC; and 2) Proprietary Texas Children's Hospital Microbiome Center reference databases and state-of-the art bioinformatics approaches (e.g., supervised learning, bipartite, Bayesian models) to identify disorder-specific biomarkers and therapeutic targets within children with FGIDs: Sub-Aim 2a - Characterize the relationships between `omics and abdominal pain symptoms (and stooling symptoms in IBS). Sub-Aim 2b ? Characterize the relationships between `omics and abnormal physiology (impaired barrier function, neuroimmune dysfunction). It is anticipated that this innovative, multidisciplinary study will better inform patient management and offer unique therapeutic strategies based on novel insights provided by FGID biomarkers. The goals of this application fit with NINR PA- 18-140, the recently published NINR Symptom Science Model, and the NIH Common Fund and Precision Medicine Initiatives.